The accuracy of an automated transcription of audio data can be improved through the use of one or more models that are tailored to or reflect one or more of the subjects in the audio data. In the exemplary embodiment of a customer service call center, the audio data is a recording or a stream of a customer service interaction between a customer service agent and a customer. In many cases the customer service interaction will pertain to specific technology, complaints, customer services, or other issues that are related to the produces or services offered by a company. In a merely exemplary embodiment, a company in the cellular communications business may have customer service interactions related to particular devices (e.g. cell phones), customer complaints (e.g. billing dispute), or specific customer service activity (e.g. add, modify, or cancel service). A model may be created to reflect these topics or specialized vocabulary related to these topics that arise in the customer service interactions greater than these topics or vocabulary arise in a generalized model of speech communication. In another embodiment, a customer service call center may specifically focus on interactions with customers from a particular country or region and those customers may use a distinct vocabulary (e.g. language or dialect) in customer service interactions.
Currently, the creation of these topically or regionally adapted models is expensive and time consuming as these models rely upon manual transcriptions in order to ensure that the transcription is correct and then these manually transcribed customer service interactions can be extrapolated into adapted models.